Investigating the Contribution of Collagen to the Tumor Biomechanical Phenotype with Noninvasive Magnetic Resonance Elastography

Assessment of Tumor Cell Invasion and Radiotherapy Response in Experimental Glioma by Magnetic Resonance Elastography

BACKGROUND

Gliomas are highly invasive brain neoplasms. MRI is the most important tool to diagnose and monitor glioma but has shortcomings. In particular, the assessment of tumor cell invasion is insufficient. This is a clinical dilemma, as recurrence can arise from MRI-occult glioma cell invasion.

HYPOTHESIS

Tumor cell invasion, tumor growth and radiotherapy alter the brain parenchymal microstructure and thus are assessable by diffusion tensor imaging (DTI) and MR elastography (MRE).

STUDY TYPE

Experimental, animal model.

ANIMAL MODEL

Twenty-three male NMRI nude mice orthotopically implanted with S24 patient-derived glioma cells (experimental mice) and 9 NMRI nude mice stereotactically injected with 1 μL PBS (sham-injected mice).

FIELD STRENGTH/SEQUENCE

2D and 3D T2-weighted rapid acquisition with refocused echoes (RARE), 2D echo planar imaging (EPI) DTI, 2D multi-slice multi-echo (MSME) T2 relaxometry, 3D MSME MRE at 900 Hz acquired at 9.4 T (675 mT/m gradient strength).

ASSESSMENT

Longitudinal 4-weekly imaging was performed for up to 4 months. Tumor volume was assessed in experimental mice (n = 10 treatment-control, n = 13 radiotherapy). The radiotherapy subgroup and 5 sham-injected mice underwent irradiation (3 × 6 Gy) 9 weeks post-implantation/sham injection. MRI-/MRE-parameters were assessed in the corpus callosum and tumor core/injection tract. Imaging data were correlated to light sheet microscopy (LSM) and histology.

STATISTICAL TESTS

Paired and unpaired t-tests, a P-value ≤0.05 was considered significant.

RESULTS

From week 4 to 8, a significant callosal stiffening (4.44 ± 0.22 vs. 5.31 ± 0.29 kPa) was detected correlating with LSM-proven tumor cell invasion. This was occult to all other imaging metrics. Histologically proven tissue destruction in the tumor core led to an increased T2 relaxation time (41.65 ± 0.34 vs. 44.83 ± 0.66 msec) and ADC (610.2 ± 12.27 vs. 711.2 ± 13.42 × 10-6 mm2/s) and a softening (5.51 ± 0.30 vs. 4.24 ± 0.29 kPa) from week 8 to 12. Radiotherapy slowed tumor progression.

DATA CONCLUSION

MRE is promising for the assessment of key glioma characteristics.

EVIDENCE LEVEL

NA TECHNICAL EFFICACY: Stage 2.

Magnetic Resonance Elastography of Invasive Breast Cancer: Evaluating Prognostic Factors and Treatment Response

Objectives: To assess the elasticity values in breast tissues using magnetic resonance elastography (MRE) and examine the association between elasticity values of invasive breast cancer with prognostic factors and the pathologic response to neoadjuvant systemic therapy (NST). Methods: A total of 57 patients (mean age, 54.1 years) with invasive breast cancers larger than 2 cm in diameter on ultrasound were prospectively enrolled. The elasticity values (mean, minimum, and maximum) of invasive breast cancers, normal fibroglandular tissues, and normal fat tissues were measured via MRE using a commercially available acoustic driver and compared. Elasticity values of breast cancers were compared according to prognostic factors and pathologic responses in patients who received NST before surgery. Receiver operating curve analysis was performed to evaluate the predictive efficacy of elasticity values in terms of pathological response. Results: Among the 57 patients, the mean elasticity value of invasive breast cancers was significantly higher than that of normal fibroglandular tissue and normal fat tissue (7.90 ± 5.80 kPa vs. 2.54 ± 0.80 kPa vs. 1.32 ± 0.33 kPa, all ps < 0.001). Invasive breast cancers with a large diameter (>4 cm) exhibited significantly higher mean elasticity values relative to tumors with a small diameter (≤4 cm) (11.65 ± 7.22 kPa vs. 5.87 ± 3.58 kPa, p = 0.002). Among 24 patients who received NST, mean, minimum, and maximum elasticity values significantly differed between the pathologic complete response (pCR) and non-pCR groups (all ps < 0.05). For the mean elasticity value, the area under the curve value for distinguishing pCR and non-pCR groups was 0.880 (95% confidence interval, 0.682, 0.976; p < 0.001). Conclusions: The elasticity values of invasive breast cancers measured via breast MRE showed a positive correlation with tumor size and showed potential in predicting the therapeutic response in patients receiving NST.

Prediction of clinically relevant postoperative pancreatic fistula after pancreatoduodenectomy based on multifrequency magnetic resonance elastography

BACKGROUND

Clinically relevant postoperative pancreatic fistula (CR-POPF) is the major complication of pancreatoduodenectomy, and the pancreatic texture is one of the potential affecting factors. Multifrequency magnetic resonance elastography (MRE) is a novel technique for measuring tissue stiffness, but its value in predicting CR-POPF preoperatively has not been well documented.

METHODS

A total of 70 patients who underwent multifrequency MRE before pancreatoduodenectomy between July 2021 and April 2024 were retrospectively recruited into the study. The parameters of MRE, shear wave speed (c) and phase angle (φ), and clinical data were collected. Logistic regression and the receiver operating characteristic curve analyses were used to assess the performance of multifrequency MRE in predicting CR-POPF.

RESULTS

CR-POPF was developed in 14 of 70 patients (20%), all categorized as grade B. The CR-POPF group had significantly lower c (1.339 ± 0.210 m/s) and longer hospital stays (21 [IQR, 15.50-37.75] days) than the no-CR-POPF group. The MRE parameters, c and φ, were moderately correlated with pancreas stiffness (eta2 for φ = 0.189 and eta2 for c = 0.106). Dilated major pancreatic duct (MPD ≥ 3 mm) and higher c were independently associated with a lower risk of CR-POPF in univariant and multivariant analyses (odds ratio [OR] for c, 0.041 [95% CI, 0.002-0.879]; OR for dilated MPD, 0.129 [95% CI, 0.022-0.768]). The area under the curve (AUC) of the predictive model based on c and MPD diameter was 0.786, which was better than the fistula risk score (FRS) (AUC = 0.587) and alternative FRS (AUC = 0.556) in our center, with the DeLong test P = .028 and P = .002, respectively.

CONCLUSION

The MRE parameters were associated with pancreatic stiffness, and c was an independent predictor of CR-POPF after pancreatoduodenectomy.

Magnetic Resonance Elastography for Breast Cancer Diagnosis Through the Assessment of Tissue Biomechanical Properties

Background and Aim

Breast cancer and normal breast tissue exhibit different degrees of stiffness, indicating distinct biomechanical properties. Study results reveal that breast cancer tissue is several times stiffer than normal breast tissue. These variations can serve as indicative factors for imaging purposes. Depicting markers can significantly enhance the process of breast cancer diagnosis and treatment. This article provides a brief review of the biomechanical properties of breast cancer tissue, highlighting the role of the magnetic resonance elastography (MRE) technique in utilizing these properties for diagnosing breast cancer.

Methods

In breast MRE, low-frequency shear waves are employed to measure breast stiffness. This method not only offers a quantitative diagnosis but also generates an elastogram, determining the stiffness of each area through its colors.

Results

MRE represents a diagnostic technique with heightened sensitivity, based on depicting the viscoelasticity properties of breast tissue and describing tumors in terms of biomechanical properties. Combining tissue biomechanical properties, such as tissue stiffness, with contrast-enhanced breast Magnetic Resonance Imaging (MRI) leads to tumor diagnosis. The value of MRE in oncological imaging aims at the early detection of tumors and evaluating the prognosis of breast cancer.

Conclusion

Breast MRE can identify the reduction of interstitial pressure in tumors by detecting changes in tissue stiffness, making it an effective tool for monitoring treatment responses. This technique is safe, repeatable, and highly precise, significantly aiding in patient screening.

Evaluation of pancreatic iodine uptake and related influential factors in multiphase dual-energy CT

OBJECTIVES

To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).

MATERIALS AND METHODS

This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s-40 s, 60 s-70 s, and 150 s-180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.

RESULTS

A total of 562 participants (median age 58 years [interquartile range: 47-67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = -0.240, p = 0.001), and type-II diabetes (β = -0.449, p < 0.001); NICPP by VFA (β = -0.301, p = 0.017) and smoking (β = -0.291, p < 0.001); and NICEP by smoking (β = -0.154, p = 0.10) and alcohol consumption (β = -0.350, p < 0.001) with statistical power values over 0.81.

CONCLUSION

NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.

CLINICAL RELEVANCE STATEMENT

This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.

KEY POINTS

Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies. Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake. Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.

In vivo characterization of brain tumor biomechanics: magnetic resonance elastography in intracranial B16 melanoma and GL261 glioma mouse models

Introduction

Magnetic Resonance Elastography (MRE) allows the non-invasive quantification of tumor biomechanical properties in vivo. With increasing incidence of brain metastases, there is a notable absence of appropriate preclinical models to investigate their biomechanical characteristics. Therefore, the purpose of this work was to assess the biomechanical characteristics of B16 melanoma brain metastases (MBM) and compare it to murine GL261 glioblastoma (GBM) model using multifrequency MRE with tomoelastography post processing.

Methods

Intracranial B16 MBM (n = 6) and GL261 GBM (n = 7) mouse models were used. Magnetic Resonance Imaging (MRI) was performed at set intervals after tumor implantation: 5, 7, 12, 14 days for MBM and 13 and 22 days for GBM. The investigations were performed using a 7T preclinical MRI with 20 mm head coil. The protocol consisted of single-shot spin echo-planar multifrequency MRE with tomoelastography post processing, contrast-enhanced T1- and T2-weighted imaging and diffusion-weighted imaging (DWI) with quantification of apparent diffusion coefficient of water (ADC). Elastography quantified shear wave speed (SWS), magnitude of complex MR signal (T2/T2*) and loss angle (φ). Immunohistological investigations were performed to assess vascularization, blood-brain-barrier integrity and extent of glucosaminoglucan coverage.

Results

Volumetric analyses displayed rapid growth of both tumor entities and softer tissue properties than healthy brain (healthy: 5.17 ± 0.48, MBM: 3.83 ± 0.55, GBM: 3.7 ± 0.23, [m/s]). SWS of MBM remained unchanged throughout tumor progression with decreased T2/T2* intensity and increased ADC on days 12 and 14 (p<0.0001 for both). Conversely, GBM presented reduced φ values on day 22 (p=0.0237), with no significant alterations in ADC. Histological analysis revealed substantial vascularization and elevated glycosaminoglycan content in both tumor types compared to healthy contralateral brain.

Discussion

Our results indicate that while both, MBM and GBM, exhibited softer properties compared to healthy brain, imaging and histological analysis revealed different underlying microstructural causes: hemorrhages in MBM and increased vascularization and glycosaminoglycan content in GBM, further corroborated by DWI and T2/T2* contrast. These findings underscore the complementary nature of MRE and its potential to enhance our understanding of tumor characteristics when used alongside established techniques. This comprehensive approach could lead to improved clinical outcomes and a deeper understanding of brain tumor pathophysiology.

Tumor biomechanics as a novel imaging biomarker to assess response to immunotherapy in a murine glioma model

Glioblastoma is the most common and aggressive primary malignant brain tumor with poor prognosis. Novel immunotherapeutic approaches are currently under investigation. Even though magnetic resonance imaging (MRI) is the most important imaging tool for treatment monitoring, response assessment is often hampered by therapy-related tissue changes. As tumor and therapy-associated tissue reactions differ structurally, we hypothesize that biomechanics could be a pertinent imaging proxy for differentiation. Longitudinal MRI and magnetic resonance elastography (MRE) were performed to monitor response to immunotherapy with a toll-like receptor 7/8 agonist in orthotopic syngeneic experimental glioma. Imaging results were correlated to histology and light sheet microscopy data. Here, we identify MRE as a promising non-invasive imaging method for immunotherapy-monitoring by quantifying changes in response-related tumor mechanics. Specifically, we show that a relative softening of treated compared to untreated tumors is linked to the inflammatory processes following therapy-induced re-education of tumor-associated myeloid cells. Mechanistically, combined effects of myeloid influx and inflammation including extracellular matrix degradation following immunotherapy form the basis of treated tumors being softer than untreated glioma. This is a very early indicator of therapy response outperforming established imaging metrics such as tumor volume. The overall anti-tumor inflammatory processes likely have similar effects on human brain tissue biomechanics, making MRE a promising tool for gauging response to immunotherapy in glioma patients early, thereby strongly impacting patient pathway.

Impact of pre-treatment extracellular volume fraction measured by computed tomography on response of primary lesion to preoperative chemotherapy in abdominal neuroblastoma

OBJECTIVES

To retrospectively investigate the impact of pre-treatment Extracellular Volume Fraction (ECV) measured by Computed Tomography (CT) on the response of primary lesions to preoperative chemotherapy in abdominal neuroblastoma.

METHODS

A total of seventy-five patients with abdominal neuroblastoma were retrospectively included in the study. The regions of interest for the primary lesion and aorta were determined on unenhanced and equilibrium phase CT images before treatment, and their average CT values were measured. Based on patient hematocrit and average CT values, the ECV was calculated. The correlation between ECV and the reduction in primary lesion volume was examined. A receiver operating characteristic curve was generated to assess the predictive performance of ECV for a very good partial response of the primary lesion.

RESULTS

There was a negative correlation between primary lesion volume reduction and ECV (r = -0.351, p = 0.002), and primary lesions with very good partial response had lower ECV (p < 0.001). The area under the curve for ECV in predicting the very good partial response of primary lesion was 0.742 (p < 0.001), with a 95 % Confidence Interval of 0.628 to 0.836. The optimal cut-off value was 0.28, and the sensitivity and specificity were 62.07 % and 84.78 %, respectively.

CONCLUSIONS

The measurement of pre-treatment ECV on CT images demonstrates a significant correlation with the response of the primary lesion to preoperative chemotherapy in abdominal neuroblastoma.

Sensitivity of magnetic resonance elastography to extracellular matrix and cell motility in human prostate cancer cell line-derived xenograft models

Prostate cancer (PCa) is a significant health problem in the male population of the Western world. Magnetic resonance elastography (MRE), an emerging medical imaging technique sensitive to mechanical properties of biological tissues, detects PCa based on abnormally high stiffness and viscosity values. Yet, the origin of these changes in tissue properties and how they correlate with histopathological markers and tumor aggressiveness are largely unknown, hindering the use of tumor biomechanical properties for establishing a noninvasive PCa staging system. To infer the contributions of extracellular matrix (ECM) components and cell motility, we investigated fresh tissue specimens from two PCa xenograft mouse models, PC3 and LNCaP, using magnetic resonance elastography (MRE), diffusion-weighted imaging (DWI), quantitative histology, and nuclear shape analysis. Increased tumor stiffness and impaired water diffusion were observed to be associated with collagen and elastin accumulation and decreased cell motility. Overall, LNCaP, while more representative of clinical PCa than PC3, accumulated fewer ECM components, induced less restriction of water diffusion, and exhibited increased cell motility, resulting in overall softer and less viscous properties. Taken together, our results suggest that prostate tumor stiffness increases with ECM accumulation and cell adhesion - characteristics that influence critical biological processes of cancer development. MRE paired with DWI provides a powerful set of imaging markers that can potentially predict prostate tumor development from benign masses to aggressive malignancies in patients. STATEMENT OF SIGNIFICANCE: Xenograft models of human prostate tumor cell lines, allowing correlation of microstructure-sensitive biophysical imaging parameters with quantitative histological methods, can be investigated to identify hallmarks of cancer.

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

Tumor Stiffness Measurement at Multifrequency MR Elastography to Predict Lymphovascular Space Invasion in Endometrial Cancer

Background Pathologic lymphovascular space invasion (LVSI) is associated with poor outcome in endometrial cancer. Its relationship with tumor stiffness, which can be measured with use of MR elastography, has not been extensively explored. Purpose To assess whether MR elastography-based mechanical characteristics can aid in the noninvasive prediction of LVSI in patients with endometrial cancer. Materials and Methods This prospective study included consecutive adult patients with a suspected uterine tumor who underwent MRI and MR elastography between October 2022 and July 2023. A region of interest delineated on T2-weighted magnitude images was duplicated on MR elastography images and used to calculate c (stiffness in meters per second) and φ (viscosity in radians) values. Pathologic assessment of hysterectomy specimens for LVSI served as the reference standard. Data were compared between LVSI-positive and -negative groups with use of the Mann-Whitney U test. Multivariable logistic regression was used to determine variables associated with LVSI positivity and develop diagnostic models for predicting LVSI. Model performance was assessed with use of area under the receiver operating characteristic curve (AUC) and compared using the DeLong test. Results A total of 101 participants were included, 72 who were LVSI-negative (median age, 53 years [IQR, 48-62 years]) and 29 who were LVSI-positive (median age, 54 years [IQR, 49-60 years]). The tumor stiffness in the LVSI-positive group was higher than in the LVSI-negative group (median, 4.1 m/sec [IQR, 3.2-4.6 m/sec] vs 2.2 m/sec [IQR, 2.0-2.8 m/sec]; P < .001). Tumor volume, cancer antigen 125 level, and tumor stiffness were associated with LVSI positivity (adjusted odds ratio range, 1.01-9.06; P range, <.001-.04). The combined model (AUC, 0.93) showed better performance for predicting LVSI compared with clinical-radiologic model (AUC, 0.77; P = .003) and similar performance to the MR elastography-based model (AUC, 0.89; P = .06). Conclusion The addition of tumor stiffness as measured at MR elastography into a clinical-radiologic model improved prediction of LVSI in patients with endometrial cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Ehman in this issue.

MR Elastography of the Pancreas: Bowel Preparation and Repeatability Assessment in Pancreatic Cancer Patients and Healthy Controls

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) stromal viscoelasticity can be measured using MR elastography (MRE). Bowel preparation regimens could affect MRE quality and knowledge on repeatability is crucial for clinical implementation.

PURPOSE

To assess effects of four bowel preparation regimens on MRE quality and to evaluate repeatability and differentiate patients from healthy controls.

STUDY TYPE

Prospective.

POPULATION

15 controls (41 ± 16 years; 47% female), 16 PDAC patients (one excluded, 66 ± 12 years; 40% female) with 15 age-/sex-matched controls (65 ± 11 years; 40% female). Final sample size was 25 controls and 15 PDAC.

FIELD STRENGTH/SEQUENCE

3-T, spin-echo echo-planar-imaging, turbo spin-echo, and fast field echo gradient-echo.

ASSESSMENT

Four different regimens were used: fasting; scopolaminebutyl; drinking 0.5 L water; combination of 0.5 L water and scopolaminebutyl. MRE signal-to-noise ratio (SNR) was compared between all regimens. MRE repeatability (test-retest) and differences in shear wave speed (SWS) and phase angle (ϕ) were assessed in PDAC and controls. Regions-of-interest were defined for tumor, nontumorous (n = 8) tissue in PDAC, and whole pancreas in controls. Two radiologists delineated tumors twice for evaluation of intraobserver and interobserver variability.

STATISTICAL TESTS

Repeated measures analysis of variance, coefficients of variation (CoVs), Bland-Altman analysis, (un)paired t-test, Mann-Whitney U-test, and Wilcoxon signed-rank test. P-value<0.05 was considered statistically significant.

RESULTS

Preparation regimens did not significantly influence MRE-SNR. Therefore, the least burdensome preparation (fasting only) was continued. CoVs for tumor SWS were: intrasession (12.8%) and intersession (21.7%), and intraobserver (7.9%) and interobserver (10.3%) comparisons. For controls, CoVs were intrasession (4.6%) and intersession (6.4%). Average SWS for tumor, nontumor, and healthy tissue were: 1.74 ± 0.58, 1.38 ± 0.27, and 1.18 ± 0.16 m/sec (ϕ: 1.02 ± 0.17, 0.91 ± 0.07, and 0.85 ± 0.08 rad), respectively. Significant differences were found between all groups, except for ϕ between healthy-nontumor (P = 0.094).

DATA CONCLUSION

The proposed bowel preparation regimens may not influence MRE quality. MRE may be able to differentiate between healthy tissue-tumor and tumor-nontumor.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY STAGE: 2.

Correlations between contrast-enhanced CT-measured extracellular volume fraction, histopathological features, and MYCN amplification status in abdominal neuroblastoma: a retrospective study

PURPOSE

To retrospectively investigate the correlations between contrast-enhanced CT (CECT)-measured extracellular volume fraction (fECV) and histopathological features, as well as MYCN amplification status, in abdominal neuroblastoma.

MATERIALS AND METHODS

One hundred and forty-one patients with abdominal neuroblastoma who underwent CECT scanning were retrospectively enrolled. Calculation of fECV involved the measurement of CT values within regions of interest located within the neuroblastoma and aorta on both non-contrast-enhanced CT and equilibrium CECT. The correlations between fECV and various factors, including pathological subtype, mitosis karyorrhexis index (MKI), Shimada classification, MYCN amplification status, International Neuroblastoma Risk Group (INRG) stage, and risk group were analyzed using either the Mann-Whitney U test or Kruskal-Wallis test.

RESULTS

Neuroblastoma and ganglioneuroblastoma exhibited fECV values of 0.349 (0.252, 0.424) and 0.438 (0.327, 0.508), respectively, indicating a statistically significant difference (Z = 2.200, P = 0.028). Additionally, the fECV decreased significantly in neuroblastoma with high MKI (H = 8.314, P = 0.016) or unfavorable histology (Z = 3.880, P < 0.001), as well as in those with MYCN amplification (Z = 5.486, P < 0.001). Notably, a significant variation in fECV was observed among different INRG stages (H = 16.881, P <0.001) and risk groups (H = 29.014, P < 0.001).

CONCLUSION

CECT-derived fECV is associated with histopathological features, MYCN amplification status, INRG stage, and risk stratification of abdominal neuroblastoma, reflecting a potential correlation between the extracellular matrix and the biological behavior of neuroblastoma.

Changes in Tissue Fluidity Predict Tumor Aggressiveness In Vivo

Cancer progression is caused by genetic changes and associated with various alterations in cell properties, which also affect a tumor's mechanical state. While an increased stiffness has been well known for long for solid tumors, it has limited prognostic power. It is hypothesized that cancer progression is accompanied by tissue fluidization, where portions of the tissue can change position across different length scales. Supported by tabletop magnetic resonance elastography (MRE) on stroma mimicking collagen gels and microscopic analysis of live cells inside patient derived tumor explants, an overview is provided of how cancer associated mechanisms, including cellular unjamming, proliferation, microenvironment composition, and remodeling can alter a tissue's fluidity and stiffness. In vivo, state-of-the-art multifrequency MRE can distinguish tumors from their surrounding host tissue by their rheological fingerprints. Most importantly, a meta-analysis on the currently available clinical studies is conducted and universal trends are identified. The results and conclusions are condensed into a gedankenexperiment about how a tumor can grow and eventually metastasize into its environment from a physics perspective to deduce corresponding mechanical properties. Based on stiffness, fluidity, spatial heterogeneity, and texture of the tumor front a roadmap for a prognosis of a tumor's aggressiveness and metastatic potential is presented.

Multi-frequency shear modulus measurements discriminate tumorous from healthy tissues

As far as their mechanical properties are concerned, cancerous lesions can be confused with healthy surrounding tissues in elastography protocols if only the magnitude of moduli is considered. We show that the frequency dependence of the tissue's mechanical properties allows for discriminating the tumor from other tissues, obtaining a good contrast even when healthy and tumor tissues have shear moduli of comparable magnitude. We measured the shear modulus G^*(ω) of xenograft subcutaneous tumors developed in mice using breast human cancer cells, compared with that of fat, skin and muscle harvested from the same mice. As the absolute shear modulus |G^*(ω)| of tumors increases by 42% (from 5.2 to 7.4 kPa) between 0.25 and 63 Hz, it varies over the same frequency range by 77% (from 0.53 to 0.94 kPa) for the fat, by 103% (from 3.4 to 6.9 kPa) for the skin and by 120% (from 4.4 to 9.7 kPa) for the muscle. These measurements fit well to the fractional model G^*(ω)=K(iω)ⁿ, yielding a coefficient K and a power-law exponent n for each sample. Tumor, skin and muscle have comparable K parameter values, that of fat being significantly lower; the p-values given by a Mann-Whitney test are above 0.14 when comparing tumor, skin and muscle between themselves, but below 0.001 when comparing fat with tumor, skin or muscle. With regards the n parameter, tumor and fat are comparable, with p-values above 0.43, whereas tumor differs from both skin and muscle, with p-values below 0.001. Tumor tissues thus significantly differs from fat, skin and muscle on account of either the K or the n parameter, i.e. of either the magnitude or the frequency-dependence of the shear modulus.

Micro-mechanical fingerprints of the rat bladder change in actinic cystitis and tumor presence

Tissue mechanics determines tissue homeostasis, disease development and progression. Bladder strongly relies on its mechanical properties to perform its physiological function, but these are poorly unveiled under normal and pathological conditions. Here we characterize the mechanical fingerprints at the micro-scale level of the three tissue layers which compose the healthy bladder wall, and identify modifications associated with the onset and progression of pathological conditions (i.e., actinic cystitis and bladder cancer). We use two indentation-based instruments (an Atomic Force Microscope and a nanoindenter) and compare the micromechanical maps with a comprehensive histological analysis. We find that the healthy bladder wall is a mechanically inhomogeneous tissue, with a gradient of increasing stiffness from the urothelium to the lamina propria, which gradually decreases when reaching the muscle outer layer. Stiffening in fibrotic tissues correlate with increased deposition of dense extracellular matrix in the lamina propria. An increase in tissue compliance is observed before the onset and invasion of the tumor. By providing high resolution micromechanical investigation of each tissue layer of the bladder, we depict the intrinsic mechanical heterogeneity of the layers of a healthy bladder as compared with the mechanical properties alterations associated with either actinic cystitis or bladder tumor.

High frequency ultrasound vibrational shear wave elastography for preclinical research

Preclinical evaluation of novel therapies using models of cancer is an important tool in cancer research, where imaging can provide non-invasive tools to characterise the internal structure and function of tumours. The short propagation paths when imaging tumours and organs in small animals allow the use of high frequencies for both ultrasound and shear waves, providing the opportunity for high-resolution shear wave elastography and hence its use for studying the heterogeneity of tissue elasticity, where heterogeneity may be a predictor of tissue response. Here we demonstrate vibrational shear wave elastography (VSWE) using a mechanical actuator to produce high frequency (up to 1000 Hz) shear waves in preclinical tumours, an alternative to the majority of preclinical ultrasound SWE studies where an acoustic radiation force impulse is required to create a relatively low-frequency broad-band shear-wave pulse. We implement VSWE with a high frequency (17.8 MHz) probe running a focused line-by-line ultrasound imaging sequence which as expected was found to offer improved detection of 1000 Hz shear waves over an ultrafast planar wave imaging sequence in a homogenous tissue-mimicking phantom. We test the VSWE in anex vivotumour xenograft, demonstrating the ability to detect shear waves up to 10 mm from the contactor position at 1000 Hz. By reducing the kernel size used for shear wave speed estimation to 1 mm we are able to produce shear wave speed images with spatial resolution of this order. Finally, we present VSWE data from xenograft tumoursin vivo, demonstrating the feasibility of the technique in mice under isoflurane sedation. Mean shear wave speeds in the tumours are in good agreements with those reported by previous authors. Characterising the frequency dependence of shear wave speed demonstrates the potential to quantify the viscoelastic properties of tumoursin vivo.

Predicting treatment response to concurrent chemoradiotherapy in squamous cell carcinoma of the cervix using amide proton transfer imaging and intravoxel incoherent motion imaging

PURPOSE

The purpose of this study was to investigate whether amide proton transfer (APT) imaging and intravoxel incoherent motion (IVIM) imaging can predict tumor response to concurrent chemoradiotherapy (CCRT) in patients with squamous cell carcinoma of the cervix (SCCC).

MATERIAL AND METHODS

Fifty-nine women (mean age, 54 years ± 10 [standard deviation] years; age range: 32-81 years) with pathologically confirmed SCCC underwent magnetic resonance imaging examination of the pelvis including APT and IVIM before concurrent chemoradiotherapy. They were divided into complete remission (CR) and non-CR groups according to therapeutic effect. APT values and IVIM-derived parameters were measured. Intra- and interobserver agreement for IVIM and APT parameters was assessed using intraclass correlation coefficient (ICC) The independent samples t-test was performed to compare the evaluated parameters between the two groups. Predictive performance for treatment response was evaluated by receiver operator characteristic (ROC) curve analysis.

RESULTS

There were 38 and 21 patients in the non-CR and CR groups, respectively. Excellent interobserver and intraobserver agreement were obtained for all IVIM and APT parameters, with ICCs ranging from 0.844 to 0.962. Perfusion fraction (f) and APT values were lower in the CR group compared with the non-CR group (both P < 0.05). The combination of f and APT values showed good diagnostic performances in predicting response to concurrent chemoradiotherapy, with an area under the ROC curve of 0.852 (95% CI: 0.744-0.961), 79% sensitivity (95% CI: 63-90%), 90% specificity (95% CI: 70-99%) and 83% accuracy (95% CI: 71-92%).

CONCLUSION

APT and IVIM imaging may serve as noninvasive tools for predicting response to concurrent chemoradiotherapy in patients with SCCC.

Fluid-sensitive migration mechanisms predict association between metastasis and high interstitial fluid pressure in pancreatic cancer

A remarkable feature in pancreatic cancer is the propensity to metastasize early, even for small, early stage cancers. We use a computer-based pancreatic model to simulate tumor progression behavior where fluid-sensitive migration mechanisms are accounted for as a plausible driver for metastasis. The model has been trained to comply with in vitro results to determine input parameters that characterize the migration mechanisms. To mimic previously studied preclinical xenografts we run the computer model informed with an ensemble of stochastic-generated realizations of unknown parameters related to tumor microenvironment only constrained such that pathological realistic values for interstitial fluid pressure (IFP) are obtained. The in silico model suggests the occurrence of a steady production of small clusters of cancer cells that detach from the primary tumor and form isolated islands and thereby creates a natural prerequisite for a strong invasion into the lymph nodes and venous system. The model predicts that this behavior is associated with high interstitial fluid pressure (IFP), consistent with published experimental findings. The continuum-based model is the first to explain published results for preclinical models which have reported associations between high IFP and high metastatic propensity and thereby serves to shed light on possible mechanisms behind the clinical aggressiveness of pancreatic cancer.

The "stiff rim" sign of hepatocellular carcinoma on shear wave elastography: correlation with pathological features and potential prognostic value

PURPOSE

To explore the pathologic basis, the influencing factors and potential prognostic value of the stiff rim sign in two-dimensional shear wave elastography (2D-SWE) of hepatocellular carcinoma (HCC).

METHODS

HCC patients who underwent tumor 2D-SWE examination before resection were prospectively enrolled. The stiff rim sign was defined as increased stiffness in the peritumoral region. Interobserver and intraobserver variability of the stiff rim sign was assessed. The correlation between the stiff rim sign and pathological characteristics was analyzed. Multivariate analysis was performed to examine clinical and radiological factors influencing the appearance of stiff rim sign. The Kaplan-Meier method was used to analyze the relationship between recurrence-free survival (RFS) and the stiff rim sign.

RESULTS

The stiff rim sign on 2D-SWE was present in 44.7% of HCC lesions. Interobserver agreement and intraobserver agreement for the stiff rim sign were substantial (κ = 0.772) and almost perfect (κ = 0.895), respectively. Pathologically, the stiff rim sign was associated with capsule status, capsule integrity, capsule thickness, proportion of peritumoral fibrous tissue, and peritumoral fibrous arrangement. Multivariate analysis showed that tumor size was an independent clinical predictor for the appearance of stiff rim sign (OR 1.201, p = 0.008). Kaplan-Meier analysis showed RFS was significantly poorer in the stiff rim sign (+) group than the stiff rim sign (-) group in solitary tumors smaller than 5 cm (p = 0.007) and solitary tumors with intratumoral stiffness less than 33.7 kPa (p = 0.007).

CONCLUSION

The stiff rim sign on 2D-SWE was mainly correlated with peritumoral fibrous tissue status and was a poor prognostic indicator for HCC.

The complex interactions between the cellular and non-cellular components of the brain tumor microenvironmental landscape and their therapeutic implications

Glioblastoma (GBM), an aggressive high-grade glial tumor, is resistant to therapy and has a poor prognosis due to its universal recurrence rate. GBM cells interact with the non-cellular components in the tumor microenvironment (TME), facilitating their rapid growth, evolution, and invasion into the normal brain. Herein we discuss the complexity of the interactions between the cellular and non-cellular components of the TME and advances in the field as a whole. While the stroma of non-central nervous system (CNS) tissues is abundant in fibrillary collagens, laminins, and fibronectin, the normal brain extracellular matrix (ECM) predominantly includes proteoglycans, glycoproteins, and glycosaminoglycans, with fibrillary components typically found only in association with the vasculature. However, recent studies have found that in GBMs, the microenvironment evolves into a more complex array of components, with upregulated collagen gene expression and aligned fibrillary ECM networks. The interactions of glioma cells with the ECM and the degradation of matrix barriers are crucial for both single-cell and collective invasion into neighboring brain tissue. ECM-regulated mechanisms also contribute to immune exclusion, resulting in a major challenge to immunotherapy delivery and efficacy. Glioma cells chemically and physically control the function of their environment, co-opting complex signaling networks for their own benefit, resulting in radio- and chemo-resistance, tumor recurrence, and cancer progression. Targeting these interactions is an attractive strategy for overcoming therapy resistance, and we will discuss recent advances in preclinical studies, current clinical trials, and potential future clinical applications. In this review, we also provide a comprehensive discussion of the complexities of the interconnected cellular and non-cellular components of the microenvironmental landscape of brain tumors to guide the development of safe and effective therapeutic strategies against brain cancer.

Preclinical Three-Dimensional Vibrational Shear Wave Elastography for Mapping of Tumour Biomechanical Properties In Vivo

Preclinical investigation of the biomechanical properties of tissues and their treatment-induced changes are essential to support drug-discovery, clinical translation of biomarkers of treatment response, and studies of mechanobiology. Here we describe the first use of preclinical 3D elastography to map the shear wave speed (cs), which is related to tissue stiffness, in vivo and demonstrate the ability of our novel 3D vibrational shear wave elastography (3D-VSWE) system to detect tumour response to a therapeutic challenge. We investigate the use of one or two vibrational sources at vibrational frequencies of 700, 1000 and 1200 Hz. The within-subject coefficients of variation of our system were found to be excellent for 700 and 1000 Hz and 5.4 and 6.2%, respectively. The relative change in cs measured with our 3D-VSWE upon treatment with an anti-vascular therapy ZD6126 in two tumour xenografts reflected changes in tumour necrosis. U-87 MG drug vs vehicle: Δcs = −24.7 ± 2.5 % vs 7.5 ± 7.1%, (p = 0.002) and MDA-MB-231 drug vs vehicle: Δcs = −12.3 ± 2.7 % vs 4.5 ± 4.7%, (p = 0.02). Our system enables rapid (<5 min were required for a scan length of 15 mm and three vibrational frequencies) 3D mapping of quantitative tumour viscoelastic properties in vivo, allowing exploration of regional heterogeneity within tumours and speedy recovery of animals from anaesthesia so that longitudinal studies (e.g., during tumour growth or following treatment) may be conducted frequently.

Added Value of Viscoelasticity for MRI-Based Prediction of Ki-67 Expression of Hepatocellular Carcinoma Using a Deep Learning Combined Radiomics (DLCR) Model

This study aimed to explore the added value of viscoelasticity measured by magnetic resonance elastography (MRE) in the prediction of Ki-67 expression in hepatocellular carcinoma (HCC) using a deep learning combined radiomics (DLCR) model. This retrospective study included 108 histopathology-proven HCC patients (93 males; age, 59.6 ± 11.0 years) who underwent preoperative MRI and MR elastography. They were divided into training (n = 87; 61.0 ± 9.8 years) and testing (n = 21; 60.6 ± 10.1 years) cohorts. An independent validation cohort including 43 patients (60.1 ± 11.3 years) was included for testing. A DLCR model was proposed to predict the expression of Ki-67 with cMRI, including T2W, DW, and dynamic contrast enhancement (DCE) images as inputs. The images of the shear wave speed (c-map) and phase angle (φ-map) derived from MRE were also fed into the DLCR model. The Ki-67 expression was classified into low and high groups with a threshold of 20%. Both c and φ values were ranked within the top six features for Ki-67 prediction with random forest selection, which revealed the value of MRE-based viscosity for the assessment of tumor proliferation status in HCC. When comparing the six CNN models, Xception showed the best performance for classifying the Ki-67 expression, with an AUC of 0.80 ± 0.03 (CI: 0.79-0.81) and accuracy of 0.77 ± 0.04 (CI: 0.76-0.78) when cMRI were fed into the model. The model with all modalities (MRE, AFP, and cMRI) as inputs achieved the highest AUC of 0.90 ± 0.03 (CI: 0.89-0.91) in the validation cohort. The same finding was observed in the independent testing cohort, with an AUC of 0.83 ± 0.03 (CI: 0.82-0.84). The shear wave speed and phase angle improved the performance of the DLCR model significantly for Ki-67 prediction, suggesting that MRE-based c and φ-maps can serve as important parameters to assess the tumor proliferation status in HCC.

Magnetic Resonance Elastography in Intracranial Neoplasms: A Scoping Review

BACKGROUND

Magnetic resonance elastography (MRE) allows noninvasive assessment of intracranial tumor mechanics and may thus be predictive of intraoperative conditions. Variations in the use of technical terms complicate reading of current literature, and there is need of a review using consolidated nomenclature.

OBJECTIVES

We present an overview of current literature on MRE relating to human intracranial neoplasms using standardized nomenclature suggested by the MRE guidelines committee. We then discuss the implications of the findings, and suggest approaches for future research.

METHOD

We performed a systematic literature search in PubMed, Embase, and Web of Science; the articles were screened for relevance and then subjected to full text review. Technical terms were consolidated.

RESULTS

We identified 12 studies on MRE in patients with intracranial tumors, including meningiomas, glial tumors including glioblastomas, vestibular schwannomas, hemangiopericytoma, central nervous system lymphoma, pituitary macroadenomas, and brain metastases. The studies had varying objectives that included prediction of intraoperative consistency, histological separation, prediction of adhesiveness, and exploration of the mechanobiology of tumor invasiveness and malignancy. The technical terms were translated using standardized nomenclature. The literature was highly heterogeneous in terms of image acquisition techniques, post-processing, and study design and was generally limited by small and variable cohorts.

CONCLUSIONS

MRE shows potential in predicting tumor consistency, adhesion, and mechanical homogeneity. Furthermore, MRE provides insight into malignant tumor behavior and its relation to tissue mechanics. MRE is still at a preclinical stage, but technical advances, improved understanding of soft tissue rheological impact, and larger samples are likely to enable future clinical introduction.

Atomic force microscopy reveals the mechanical properties of breast cancer bone metastases

Mechanically dependent processes are essential in cancer metastases. However, reliable mechanical characterization of metastatic cancer remains challenging whilst maintaining the tissue complexity and an intact sample. Using atomic force microscopy, we quantified the micro-mechanical properties of relatively intact metastatic breast tumours and their surrounding bone microenvironment isolated from mice, and compared with other breast cancer models both ex vivo and in vitro. A mechanical distribution of extremely low elastic modulus and viscosity was identified on metastatic tumours, which were significantly more compliant than both 2D in vitro cultured cancer cells and subcutaneous tumour explants. The presence of mechanically distinct metastatic tumour did not result in alterations of the mechanical properties of the surrounding microenvironment at meso-scale distances (>200 μm). These findings demonstrate the utility of atomic force microscopy in studies of complex tissues and provide new insights into the mechanical properties of cancer metastases in bone.

Microscopic multifrequency MR elastography for mapping viscoelasticity in zebrafish

PURPOSE

The zebrafish (Danio rerio) has become an important animal model in a wide range of biomedical research disciplines. Growing awareness of the role of biomechanical properties in tumor progression and neuronal development has led to an increasing interest in the noninvasive mapping of the viscoelastic properties of zebrafish by elastography methods applicable to bulky and nontranslucent tissues.

METHODS

Microscopic multifrequency MR elastography is introduced for mapping shear wave speed (SWS) and loss angle (φ) as markers of stiffness and viscosity of muscle, brain, and neuroblastoma tumors in postmortem zebrafish with 60 µm in-plane resolution. Experiments were performed in a 7 Tesla MR scanner at 1, 1.2, and 1.4 kHz driving frequencies.

RESULTS

Detailed zebrafish viscoelasticity maps revealed that the midbrain region (SWS = 3.1 ± 0.7 m/s, φ = 1.2 ± 0.3 radian [rad]) was stiffer and less viscous than telencephalon (SWS = 2.6 ± 0. 5 m/s, φ = 1.4 ± 0.2 rad) and optic tectum (SWS = 2.6 ± 0.5 m/s, φ = 1.3 ± 0.4 rad), whereas the cerebellum (SWS = 2.9 ± 0.6 m/s, φ = 0.9 ± 0.4 rad) was stiffer but less viscous than both (all p < .05). Overall, brain tissue (SWS = 2.9 ± 0.4 m/s, φ = 1.2 ± 0.2 rad) had similar stiffness but lower viscosity values than muscle tissue (SWS = 2.9 ± 0.5 m/s, φ = 1.4 ± 0.2 rad), whereas neuroblastoma (SWS = 2.4 ± 0.3 m/s, φ = 0.7 ± 0.1 rad, all p < .05) was the softest and least viscous tissue.

CONCLUSION

Microscopic multifrequency MR elastography-generated maps of zebrafish show many details of viscoelasticity and resolve tissue regions, of great interest in neuromechanical and oncological research and for which our study provides first reference values.

Development of three-dimensional integral-type reconstruction formula for magnetic resonance elastography

PURPOSE

The viscoelasticity (storage modulus and loss modulus) of living tissues is known to be related to diseases. Magnetic resonance elastography (MRE) is a quantitative method for non-invasive measuring viscoelasticity. The viscoelasticity is calculated from the elastic wave images using an inversion algorithm. The estimation accuracy of the inversion algorithm is degraded by background noise. This study aims to propose novel inversion algorithms that are applicable for noisy elastic wave images.

METHODS

The proposed algorithms are based on the Voigt-type viscoelastic equation. The algorithms are designed to improve the noise robustness by avoiding direct differentiation of measurement data by virtue of Green's formula. Similarly, stabilization is introduced to the curl-operator which works to eliminate the compression waves in measurement data. To clarify the characteristics of the algorithms, the proposed algorithms were compared with the conventional algorithms using isotropic and anisotropic voxel numerical simulations and phantom experimental data.

RESULTS

From the results of the numerical simulations, normalized errors of stiffness of proposed algorithms were 3% or less. The proposed algorithms mostly showed better results than the conventional algorithms despite noisy elastic wave images. From the gel phantom experiment, we confirmed the same tendency as the characteristics of the algorithms observed in the numerical simulation results.

CONCLUSION

We have developed a novel inversion algorithm and evaluated it quantitatively. The results confirm that the proposed algorithms are highly quantitative and noise-robust methods for estimating storage and loss modulus regardless of noise, voxel anisotropy, and propagation direction. Therefore, the proposed algorithms will appropriate to various three-dimensional MRE systems.

Rectal Tumor Stiffness Quantified by In Vivo Tomoelastography and Collagen Content Estimated by Histopathology Predict Tumor Aggressiveness

PURPOSE

To investigate the significance of collagen in predicting the aggressiveness of rectal tumors in patients, examined in vivo based on tomoelastography quantified stiffness and ex vivo by histologically measured collagen volume fraction (CVF).

EXPERIMENTAL DESIGN

170 patients with suspected rectal cancer were prospectively enrolled and underwent preoperative magnetic resonance imaging (MRI) and rectal tomoelastography, a technique based on multifrequency magnetic resonance elastography. Histopathologic analysis identified eighty patients with rectal cancer who were divided into subgroups by tumor-node (TN) stage, prognostic stage, and risk level. Rectal tumor stiffness was correlated with histopathologic CVF. Area-under-the-curve (AUC) and contingency analysis were used to evaluate the performance of rectal stiffness in distinguishing tumor stages which was compared to standard clinical MRI.

RESULTS

In vivo tomoelastography revealed that rectal tumor stiffened significantly with increased TN stage (p<0.05). Tumors with poorly differentiated status, perineural and lymphovascular invasion also displayed higher stiffness than well-to-moderately differentiated, noninvasive tumors (all p<0.05). Similar to in vivo stiffness, CVF indicated an abnormally high collagen content in tumors with perineural invasion and poor differentiation status. CVF was also positively correlated with stiffness (p<0.05). Most importantly, both stiffness (AUROC: 0.82) and CVF (AUROC: 0.89) demonstrated very good diagnostic accuracy in detecting rectal tumors that have high risk for progressing to an aggressive state with poorer prognosis.

CONCLUSION

In human rectal carcinomas, overexpression of collagen is correlated with increased tissue stiffness and high risk for tumor advancing more aggressively. In vivo tomoelastography quantifies rectal tumor stiffness which improves the diagnostic performance of standard MRI in the assessment of lymph nodes metastasis. Therefore, in vivo stiffness mapping by tomoelastography can predict rectal tumor aggressiveness and add diagnostic value to MRI.

A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients

BACKGROUND

The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy (nCRT) is still unknown. This study aimed to develop and validate a perdition model based on the CFs and clinicopathological characteristics to predict the treatment response to nCRT among locally advanced rectal cancer (LARC) patients.

METHODS

In this multicenter, retrospective analysis, 428 patients were included and randomly divided into a training cohort (299 patients) and validation cohort (129 patients) [7:3 ratio]. A total of 11 CFs were extracted from a multiphoton image of pretreatment biopsy, and a support vector machine (SVM) was then used to construct a CFs-SVM classifier. A prediction model was developed and presented with a nomogram using multivariable analysis. Further validation of the nomogram was performed in the validation cohort.

RESULTS

The CFs-SVM classifier, which integrated collagen area, straightness, and crosslink density, was significantly associated with treatment response. Predictors contained in the nomogram included the CFs-SVM classifier and clinicopathological characteristics by multivariable analysis. The CFs nomogram demonstrated good discrimination, with area under the receiver operating characteristic curves (AUROCs) of 0.834 in the training cohort and 0.854 in the validation cohort. Decision curve analysis indicated that the CFs nomogram was clinically useful. Moreover, compared with the traditional clinicopathological model, the CFs nomogram showed more powerful discrimination in determining the response to nCRT.

CONCLUSIONS

The CFs-SVM classifier based on CFs in the tumor microenvironment is associated with treatment response, and the CFs nomogram integrating the CFs-SVM classifier and clinicopathological characteristics is useful for individualized prediction of the treatment response to nCRT among LARC patients.

Tomoelastography for Measurement of Tumor Volume Related to Tissue Stiffness in Pancreatic Ductal Adenocarcinomas

OBJECTIVES

Estimations of tumor volume and boundary in pancreatic ductal adenocarcinoma (PDAC) are crucial for surgery planning. The aim of the study is to evaluate tomoelastography for detection of PDAC and quantification of PDAC volume based on tissue stiffness.

MATERIALS AND METHODS

From March 2018 to December 2019, a total of 102 participants (30 healthy participants and 72 patients with histologically proven PDAC) were prospectively enrolled in a multicenter study. Multifrequency magnetic resonance elastography was combined with tomoelastography postprocessing to generate maps of shear wave speed (SWS) depicting highly resolved anatomical details of tissue stiffness. Subregional analysis of pancreatic head, body, and tail and reproducibility tests were performed in healthy participants, whereas tumorous (PDAC-T) and nontumorous (PDAC-NT) pancreatic tissue analysis was conducted in patients. In all patients, tumor volumes measured by computed tomography (CT) were compared with SWS-derived volumes. In addition, in 32 patients, tumor sizes were evaluated by macroscopy after resection.

RESULTS

Tumor volumes were quantified in 99% and 87% of all cases with tomoelastography and CT, respectively. Pancreatic SWS was highly reproducible (repeatability coefficient = 0.12) and did not vary regionally or with patient age, sex, or body mass index (all P > 0.08). Shear wave speed was higher in PDAC-T (2.08 ± 0.38 m/s) than in healthy (1.25 ± 0.09 m/s; P < 0.001) and PDAC-NT (1.28 ± 0.14 m/s; P < 0.001) participants. A threshold of 1.47 m/s separated PDAC-T from healthy volunteers (area under the curve = 1.0, sensitivity = 100%, specificity = 100%), while 1.49 m/s separated PDAC-T from PDAC-NT with high accuracy (area under the curve = 0.99, sensitivity = 90%, specificity = 100%). Tomoelastography-derived tumor volume correlated with CT volume (r = 0.91, P < 0.001) and ex vivo tumor volume (r = 0.66, P < 0.001).

CONCLUSIONS

Tomoelastography provides a quantitative imaging marker for tissue stiffness depicting PDAC boundaries and separates PDAC from unaffected pancreatic tissue.

Tumor Solid Stress: Assessment with MR Elastography under Compression of Patient-Derived Hepatocellular Carcinomas and Cholangiocarcinomas Xenografted in Mice

Malignant tumors have abnormal biomechanical characteristics, including high viscoelasticity, solid stress, and interstitial fluid pressure. Magnetic resonance (MR) elastography is increasingly used to non-invasively assess tissue viscoelasticity. However, solid stress and interstitial fluid pressure measurements are performed with invasive methods. We studied the feasibility and potential role of MR elastography at basal state and under controlled compression in assessing altered biomechanical features of malignant liver tumors. MR elastography was performed in mice with patient-derived, subcutaneously xenografted hepatocellular carcinomas or cholangiocarcinomas to measure the basal viscoelasticity and the compression stiffening rate, which corresponds to the slope of elasticity versus applied compression. MR elastography measurements were correlated with invasive pressure measurements and digital histological readings. Significant differences in MR elastography parameters, pressure, and histological measurements were observed between tumor models. In multivariate analysis, collagen content and interstitial fluid pressure were determinants of basal viscoelasticity, whereas solid stress, in addition to collagen content, cellularity, and tumor type, was an independent determinant of compression stiffening rate. Compression stiffening rate had high AUC (0.87 ± 0.08) for determining elevated solid stress, whereas basal elasticity had high AUC for tumor collagen content (AUC: 0.86 ± 0.08). Our results suggest that MR elastography compression stiffening rate, in contrast to basal viscoelasticity, is a potential marker of solid stress in malignant liver tumors.

MR Elastography of the Breast: Evolution of Technique, Case Examples, and Future Directions

Recognizing that breast cancers present as firm, stiff lesions, the foundation of breast magnetic resonance elastography (MRE) is to combine tissue stiffness parameters with sensitive breast MR contrast-enhanced imaging. Breast MRE is a non-ionizing, cross-sectional MR imaging technique that provides for quantitative viscoelastic properties, including tissue stiffness, elasticity, and viscosity, of breast tissues. Currently, the technique continues to evolve as research surrounding the use of MRE in breast tissue is still developing. In the setting of a newly diagnosed cancer, associated desmoplasia, stiffening of the surrounding stroma, and necrosis are known to be prognostic factors that can add diagnostic information to patient treatment algorithms. In fact, mechanical properties of the tissue might also influence breast cancer risk. For these reasons, exploration of breast MRE has great clinical value. In this review, we will: (1) address the evolution of the various MRE techniques; (2) provide a brief overview of the current clinical studies in breast MRE with interspersed case examples; and (3) suggest directions for future research.

Influence of Fibroblasts on Mammary Gland Development, Breast Cancer Microenvironment Remodeling, and Cancer Cell Dissemination

The stromal microenvironment regulates mammary gland development and tumorigenesis. In normal mammary glands, the stromal microenvironment encompasses the ducts and contains fibroblasts, the main regulators of branching morphogenesis. Understanding the way fibroblast signaling pathways regulate mammary gland development may offer insights into the mechanisms of breast cancer (BC) biology. In fact, the unregulated mammary fibroblast signaling pathways, associated with alterations in extracellular matrix (ECM) remodeling and branching morphogenesis, drive breast cancer microenvironment (BCM) remodeling and cancer growth. The BCM comprises a very heterogeneous tissue containing non-cancer stromal cells, namely, breast cancer-associated fibroblasts (BCAFs), which represent most of the tumor mass. Moreover, the different components of the BCM highly interact with cancer cells, thereby generating a tightly intertwined network. In particular, BC cells activate recruited normal fibroblasts in BCAFs, which, in turn, promote BCM remodeling and metastasis. Thus, comparing the roles of normal fibroblasts and BCAFs in the physiological and metastatic processes, could provide a deeper understanding of the signaling pathways regulating BC dissemination. Here, we review the latest literature describing the structure of the mammary gland and the BCM and summarize the influence of epithelial-mesenchymal transition (EpMT) and autophagy in BC dissemination. Finally, we discuss the roles of fibroblasts and BCAFs in mammary gland development and BCM remodeling, respectively.

REVIEW: MR elastography of brain tumors

MR elastography allows non-invasive quantification of the shear modulus of tissue, i.e. tissue stiffness and viscosity, information that offers the potential to guide presurgical planning for brain tumor resection. Here, we review brain tumor MRE studies with particular attention to clinical applications. Studies that investigated MRE in patients with intracranial tumors, both malignant and benign as well as primary and metastatic, were queried from the Pubmed/Medline database in August 2018. Reported tumor and normal appearing white matter stiffness values were extracted and compared as a function of tumor histopathological diagnosis and MRE vibration frequencies. Because different studies used different elastography hardware, pulse sequences, reconstruction inversion algorithms, and different symmetry assumptions about the mechanical properties of tissue, effort was directed to ensure that similar quantities were used when making inter-study comparisons. In addition, because different methodologies and processing pipelines will necessarily bias the results, when pooling data from different studies, whenever possible, tumor values were compared with the same subject's contralateral normal appearing white matter to minimize any study-dependent bias. The literature search yielded 10 studies with a total of 184 primary and metastatic brain tumor patients. The group mean tumor stiffness, as measured with MRE, correlated with intra-operatively assessed stiffness of meningiomas and pituitary adenomas. Pooled data analysis showed significant overlap between shear modulus values across brain tumor types. When adjusting for the same patient normal appearing white matter shear modulus values, meningiomas were the stiffest tumor-type. MRE is increasingly being examined for potential in brain tumor imaging and might have value for surgical planning. However, significant overlap of shear modulus values between a number of different tumor types limits applicability of MRE for diagnostic purposes. Thus, further rigorous studies are needed to determine specific clinical applications of MRE for surgical planning, disease monitoring and molecular stratification of brain tumors.